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Interactive fuzzy numbers in the evaluation of the effectiveness of investment projects and selection of efficient portfolios

100%
RĘBIASZ B.
|
2010
|
vol. 20
|
issue 3-4
103-127
EN
The paper presents a method for evaluating the effectiveness and risks of investment projects and the selection of efficient portfolios in a situation where parameters in the calculation of effectiveness are expressed in the form of interactive fuzzy numbers. Fuzzy model simulations are used to perform arithmetic operations on interactive fuzzy numbers. The process of selecting investment projects takes into account statistical and economic dependences between projects.
2
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New method of selecting efficient project portfolios in the presence of hybrid uncertainty

100%
RĘBIASZ B.
Operations Research and Decisions
|
2016
|
vol. 26
|
issue 4
65-90
XX
A new methods of selecting efficient project portfolios in the presence of hybrid uncertainty has been presented. Pareto optimal solutions have been defined by an algorithm for generating project portfolios. The method presented allows us to select efficient project portfolios taking into account statistical and economic dependencies between projects when some of the parameters used in the calculation of effectiveness can be expressed in the form of an interactive possibility distribution and some in the form of a probability distribution. The procedure for processing such hybrid data combines stochastic simulation with nonlinear programming. The interaction between data are modeled by correlation matrices and the interval regression. Economic dependences are taken into account by the equations balancing the production capacity of the company. The practical example presented indicates that an interaction between projects has a significant impact on the results of calculations.
3
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Konstrukcja portfeli efektywnych z zastosowaniem Wielorównaniowych Modeli GARCH

75%
Fiszeder P.
Folia Oeconomica Cracoviensia
|
2007
|
vol. 48
47-68
EN
The purpose of this paper is to present dynamic approach to selection of efficient portfolios using a forecasts of variances and covariances from the multivariate GARCH models. Evaluation of efficiency for different methods of asset allocation is also performed for stocks from the WSE. Twelve specifications of the multivariate GARCH models, the univariate GARCH model and six other covariance matrix estimation methods are used. Taking into consideration time varying variances and covariances of stock returns in portfolio selections increases, with some exceptions, efficiency of asset allocation process. Simple specifications of them ultivariate GARCH models, w hich parameters are estimated in one stage, are the best perform ing models. From economic point of view, the differences between the models are not significant, with exception of the factor and orthogonal models. RiskMetrics methodology commonly used by practitioners does not give good results for constructions of efficient portfolios.
4
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Metoda wyboru efektywnych portfeli przedsięwzięć inwestycyjnych

63%
RĘBIASZ B.
Operations Research and Decisions
|
2009
|
vol. 19
|
issue 3
95-117
PL
W artykule przedstawiono nową metodę wyboru efektywnych portfeli przedsięwzięć inwestycyjnych. Problem wyboru portfeli sformułowano w postaci zadania optymalizacji wielokryterialnej. Opracowany algorytm umożliwia poszukiwanie niezdominowanych portfeli przedsięwzięć inwestycyjnych. Kryteriami wyboru są: maksymalizacja wartości oczekiwanej NPV i minimalizacja semiodchylenia standardowego NPV portfela. Metoda umożliwia wybór portfeli przy uwzględnieniu zależności statystycznych i ekonomicznych pomiędzy przedsięwzięciami inwestycyjnymi. Jest ona dostosowana do przedsiębiorstw o wieloetapowym cyklu produkcji, na przykład przedsiębiorstwa przemysłu metalurgicznego czy chemicznego.
EN
A new algorithm for selecting an effective investment project portfolio from a collection of projects developed by a company has been presented in this paper. The problem of selecting an investment project was formulated as multi-objective optimization problem. The algorithm is suited for enterprises with multistage production cycles, e.g. enterprises in the metallurgical or chemical industry. During the selection process the method takes into account statistical and economic interdependencies existing among projects. Upon choosing projects the algorithm takes into account twp criteria: maximization of the expected NPV and minimization of project portfolio risk. A company may develop an effective investment project portfolio for a few years ahead. The algorithm makes it possible to search for Pareto optimal solutions. It links computer simulation methods with a genetic algorithm and standard procedure for linear optimization. An example of the use of the algorithm for selecting projects in the metallurgical industry is presented.
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